parameter-variation
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npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/parameter-variationSystematically explores parameter effects using one-factor-at-a-time sweeps
- Identifies how individual parameter changes affect outcomes in a solution space
- Uses value-enumeration and combination-evaluation SOPs for structured analysis
- Prioritizes parameters by impact and evaluates variations for novelty and feasibility
- Generates sensitivity maps and variation reports for decision-making
SKILL.md
.github/skills/parameter-variationView on GitHub ↗
--- name: parameter-variation description: Systematic one-factor-at-a-time parameter sweep execution: strategy used-by: morphological-exploration --- # Parameter Variation Systematic one-factor-at-a-time (OFAT) parameter sweep to explore how individual dimension changes affect the solution space. ## State Ledger | Resource | Target | Current | % | |----------|--------|---------|---| | web-search | 20 | 0 | 0% | | web-research | 5 | 0 | 0% | | paper-overview | 20 | 0 | 0% | | paper-search | 12 | 0 | 0% | | paper-research | 5 | 0 | 0% | ## HARD-GATE Cannot exit strategy until ≥80% of each budget line is consumed OR yield targets are met with justification for remaining budget. ## Available Tactics | Tactic | Role | |--------|------| | combination-mapping | Map parameter-value combinations | ## Available SOPs | SOP | Role | |-----|------| | value-enumeration | Enumerate values for sweep | | combination-evaluation | Evaluate each variation | | path-generation | Generate sweep paths | | morphological-synthesis | Synthesize variation report | ## Execution Guidance 1. **Baseline selection**: Identify a reference configuration as baseline 2. **Parameter ordering**: Rank parameters by expected impact 3. **Sweep execution**: Vary one parameter at a time, holding others at baseline 4. **Evaluation**: Assess each variation for novelty and feasibility 5. **Sensitivity mapping**: Identify which parameters have highest creative leverage 6. **Synthesis**: Report parameter sensitivity and promising variation directions